Record divestment yet still heavily overweight tech stocks: hedge funds are compressing positions into "low-leverage certainty"

Title context: Record divestment yet still heavily overweight tech stocks: hedge funds are compressing positions into "low-leverage certainty" Text: Data from Goldman Sachs' prime brokerage division shows that hedge funds are exiting tech stocks at the fastest pace in at least a decade. Over the five trading days through October 15, the proportion of tech holdings cut by hedge funds set the largest record since Goldman began tracking the data in 2016; over the same period, overall trading activity also fell at the fastest pace in nearly three months. The reduction came as global tech stocks suffered a selloff. As the AI trade unwound globally, the Nasdaq 100 fell 5.5% last week, its worst performance since April 2025; over the five trading days covered by Goldman's data, the tech sector was also the worst performer in the MSCI World Index. Goldman data shows that global equities overall saw net selling amounting to two standard deviations of fund flows over the past year. Among them, the information technology sector led the decline by a wide margin, with the largest reduction in total holdings in two months; the semiconductor sector suffered the largest dollar-denominated losses. However, hedge funds still hold massive tech positions. Goldman's report said the net allocation to the tech sector accounted for 23.5% of its global prime brokerage book, still at the 90th percentile level of the past five years. But funds have turned more cautious, with their net leverage ratioa measure of the extent to which long positions exceed short positionsfalling to 48.6%, a one-year low. The real trigger: credit cracks in the AI financing chain, not valuations themselves The more fundamental catalyst behind the global unwinding of the AI trade is that the financing structure of AI infrastructure is exposing credit risk. Take CoreWeave as a sample: its 2032 bond spread widened past 1,000 basis points, its five-year CDS hit a record high of 1,117 basis points, implying about a 63% probability of default within five years; its stock plunged 15% in a single day, and its bond price fell below 80 cents on the dollar. Nscale's IPO also met with price pressure, with the valuation some investors argued for at a 37%47% discount to the $30 billion target. This points to a thornier problem than "valuations are too high": a structural mismatch between the spending pace and the revenue pace of AI infrastructureexpensive outlays for GPUs, data centers, and power occur first, while the revenue side must wait for power-up, acceptance testing, and actual customer activation; the higher the financing cost, the weaker a project's ability to withstand delays and underutilization. When the core of market pricing shifts from "how big is compute demand" to "who pays for the high cost of capital," the first to be sold off will inevitably be the links with the most fragile balance sheets and the greatest sensitivity to financing conditionssemiconductors, neoclouds, and highly leveraged AI namesrather than mega-cap tech companies with abundant cash flow. The essence of the disagreement: how far has deleveraging progressed The core disagreement on Wall Street today is not whether long-term AI demand exists, but whether deleveraging has largely run its course. On the more cautious side (some Goldman teams): on a one-year horizon, AI positioning appears to have been relatively cleared out; but on a three-year horizon, global net allocation to AI stocks is still at the 83rd percentile, and the AI portfolio long/short ratio of 3.27 is still at the 64th percentile. JPMorgan's TPM positioning indicator is in a neutral range at about the 46th percentile, far above the 19th percentile low at the end of July, meaning there is still room for "further deleveraging." Trading feedback from Goldman's Asia team shows that the "capitulation" in Taiwan's market during this selloff was less severe than in July, suggesting there may still be selling pressure ahead. On the more positive side (Morgan Stanley, BofA): Morgan Stanley believes the months-long valuation adjustment in most stocks is nearing its end, and after the sharp correction, mega-cap tech valuations are close to historical cycle lows, while fundamental indicators for core AI infrastructure chipsprices, orders, and earnings trendshave not yet deteriorated to a corresponding degree, and a buy-the-dip opportunity is forming after the pullback. BofA's bullish logic is similarthe market has already been discounting future financing pressure in advance, but resilient spot prices and inference demand can still support earnings expansion for a considerable time. The disagreement between the two camps boils down to one judgment: whether the credit contraction on the financing side is a substantive blow to the long-term AI narrative, or a forced cleanup of excessive leverage while the demand side itself has not deteriorated. There is a similarly balanced view within Goldmanits analyst Mark Wilson acknowledges that the "second derivative" of capex and earnings growth will slow from current levels, but stresses that prices have already reflected this expectation to a considerable degree, and cites the OpenAI CFO's statement that there is no evidence of slowing on the compute demand side. In short, the current retreat is not smart money systematically abandoning tech stocks, but rather, under the constraint of tightening financing conditions, a forced compression of positions from "high-leverage AI exposure" to "low-leverage certainty holdings." The intensity of the selling reflects the fragility of leverage, not a final verdict on the AI narrative. Therefore, for an AI stock rebound, watch for signs that junk-rated AI assets stop falling and whether the net leverage ratio stabilizes and recovers. If the one-year low of 48.6% continues to decline, it indicates deleveraging is still underway; if subsequent data show consecutive stabilization, it points to a marginal fading of selling pressure. In addition, whether the divergence between the bond market and the stock market converges is also a signal to watch. During this selloff, the 10-year Treasury yield, despite inflation exceeding expectations, instead fell back to a multi-week low, with bonds doing the Fed's tightening for it while also pricing growth risk. If credit spreads in the bond market stop widening and junk-rated AI bond yields peak and retreat, that will be a more reliable turning signal than a stock price rebound.